Course Introduction
4.8
rating6000+
students1 time
paymentAnyone
can do (IT/NonIT)Simple English
Language19 hrs
content durationLifetime
course accessSelf-paced
recorded lecturesBy getting 100% of your fees back on course completion
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Upskill↓
100% Refund4.8
rating6000+
students1 time
paymentAnyone
can do (IT/NonIT)Simple English
Language19 hrs
content durationLifetime
course accessSelf-paced
recorded lecturesonly few seats left
Ask your doubts when you want, and get it solved within 5-10 minutes
With robust Mentor Support, experience seamless learning with personal mentorship
100% Free Learning
On the courses enrolled within the 100% Refund offer through which you earn your enrollment fee back as rewardStructured Course
Learn from our structured pre recorded courses made by experts to meet industry needsInstant Mentor Support
Personal mentors to guide and help you throughout your journey as a friend through chat, calls & screen sharingProjects & Certifications
Build major projects which makes your resume stand apart alongwith course completion certificationsInternship Opportunities
Get remote internship opportunities after the completion of the course along with dedicated assignmentsLifetime Course Access
Get liftetime course access on each course that you enroll, and enjoy the benefit of mentoring wheneve you want4.8
rating68
lectures19h 52m
total durationLifetime
accessCourse Introduction
DataScience
Understanding Buzzwords
DA-Excel
DA Excel 2
DA Excel 3
Introduction to Python
Control Structures and Functions - Part 1
Data Structures - Tuples
Data Structures - Lists
Data Structures - Sets
Data Structures - Dictionary
Class and Objects
Basics of probability
Conditional and Bayes
Random Variable and Discrete Probab
Continuous Random Variables
Central Limit Theorem
Statistics in Data Science
Measures of Central Tendency
Measures of Dispersion
Hypothesis Testing
Types of errors
Regression Analysis
Underfitting Overfitting
Types of Regression Analysis
Correlation Regression
NumPy Part 1
NumPy Part 2
NumPy Part 3
NumPy Part 4
Pandas Part 1
Pandas Part 2
Matplotlib Part 1
Matplotlib Part 2
Matplotlib Part 4
Matplotlib Part 5
EDA
Matrix Vectors
Numpy, LinearAlgebra Matrix for analysis
What is a Tensor
Introduction to Deep Learning
Getting started with ML
How does ML work
Data Cleaning
Data Processing
Preprocessing in Python - Feature Scaling
Preprocessing in Python - Label Encoding
ML Classifications
ML - Regression
ML Algorithms
Classification Model
Introduction to Neural networks
How do neural networks work?
Neural Network from Scratch
Case Study - Part 1
Case Study - Part 2
Case Study - Part 3
Rainfall Prediction Part 1
Rainfall Prediction Part 2
Case Study - Tumor Detection Part 1
Case Study - Tumor Detection Part 2
The course provides the entire toolbox you need to become a data scientist
Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
Unfold the power of deep neural networks
Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
As a working professional in a big MNC, I needed to upgrade myself with data analysis and visualization, deep learning and advanced python tools. I was looking for flexible courses which can help me with my timings and then I enrolled in Tutedude. Great course with extensive curriculum, flexible timings, instant doubt-solving and lifetime access.
This was a good course, especially as someone with basically zero experience in the field. I've been struggling with where to begin, And this course gave me a good starting point. That said, it wasn't technical at all. Descriptive picture of data science. Videos are short but nicely presented which gives a student a clear idea of the subject with live one-one doubt solving sessions and mentorship.
Wanted to switch to a high paying job but didn’t have the right skills to get one. Suggested by a colleague to learn data science from Tutedude at my own pace. It has broadened my outlook about data as well as helped me to think as a Data Scientist. And now I have started getting new opportunities in this field.
I enrolled for all access pack of Tutedude and I must say that all the courses they are offering are just awesome. Have already completed 5 courses, loved the content and mentors in each course, they are very very helpful and gave me the smoothest learning experience, excited for the further courses.
The hottest carrer path of this decade.
Before understanding Data Science let's first understand importance of Data. You will be surprised to know
that 90% of the apps in your phone is using Data to take your experience to next level be it zomato, flipkart, amazon, instagram etc. Companies has tons of data with them,
I have been talking about this Data but what data is it? It is basically information about how you visit any app, what are the things you prefer, how much and when you buy etc.
Now with this data they optimize their apps for you and hence making your experience good.
Okay enough about Data, now Data Science is simply understanding this data and providing the results. Now you know what is all this buzz about Data Science and why it is soo important!
In this course we will be learning that and making you ready to handle Data of these big companies I mentioned above. Starting from very scratch we will cover thing you need to get your dream job.
What are you waiting for? Enroll Now!
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